1.1 --- a/doc/groups.dox Tue Feb 12 07:15:52 2013 +0100
1.2 +++ b/doc/groups.dox Fri Mar 01 17:59:08 2013 +0100
1.3 @@ -558,6 +558,42 @@
1.4 \image html planar.png
1.5 \image latex planar.eps "Plane graph" width=\textwidth
1.6 */
1.7 +
1.8 +/**
1.9 +@defgroup tsp Traveling Salesman Problem
1.10 +@ingroup algs
1.11 +\brief Algorithms for the symmetric traveling salesman problem
1.12 +
1.13 +This group contains basic heuristic algorithms for the the symmetric
1.14 +\e traveling \e salesman \e problem (TSP).
1.15 +Given an \ref FullGraph "undirected full graph" with a cost map on its edges,
1.16 +the problem is to find a shortest possible tour that visits each node exactly
1.17 +once (i.e. the minimum cost Hamiltonian cycle).
1.18 +
1.19 +These TSP algorithms are intended to be used with a \e metric \e cost
1.20 +\e function, i.e. the edge costs should satisfy the triangle inequality.
1.21 +Otherwise the algorithms could yield worse results.
1.22 +
1.23 +LEMON provides five well-known heuristics for solving symmetric TSP:
1.24 + - \ref NearestNeighborTsp Neareast neighbor algorithm
1.25 + - \ref GreedyTsp Greedy algorithm
1.26 + - \ref InsertionTsp Insertion heuristic (with four selection methods)
1.27 + - \ref ChristofidesTsp Christofides algorithm
1.28 + - \ref Opt2Tsp 2-opt algorithm
1.29 +
1.30 +\ref NearestNeighborTsp, \ref GreedyTsp, and \ref InsertionTsp are the fastest
1.31 +solution methods. Furthermore, \ref InsertionTsp is usually quite effective.
1.32 +
1.33 +\ref ChristofidesTsp is somewhat slower, but it has the best guaranteed
1.34 +approximation factor: 3/2.
1.35 +
1.36 +\ref Opt2Tsp usually provides the best results in practice, but
1.37 +it is the slowest method. It can also be used to improve given tours,
1.38 +for example, the results of other algorithms.
1.39 +
1.40 +\image html tsp.png
1.41 +\image latex tsp.eps "Traveling salesman problem" width=\textwidth
1.42 +*/
1.43
1.44 /**
1.45 @defgroup approx_algs Approximation Algorithms